Abstract
People spend approximately 80% of their time indoors, which is why indoor air quality is important for human health in recent years. Instant determination of the changing indoor air quality, especially in public buildings, and implementing appropriate prevention measures is therefore necessary. One of the most important air pollutants is total volatile organic compounds. The purpose of this study was to measure simultaneously the concentration of total volatile organic compounds by two different methods; wireless sensor and passive sampling. The passive sampling period was chosen as one week, so samples were collected 4 times in one month. Passive samples were collected using Radiello stainless steel tubes in two different laboratories and were analyzed by thermal desorber and gas chromatography-mass spectrometer instrumentals. In the wireless sensor networks, data were collected every minute for a month at the same points in the same laboratories. The two methods were compared and the observed accuracy of the methods was about 5.89%. The classical method (passive sampling) is expensive and the result isn’t prepared on time. In this paper, we offer a low-cost indoor air quality monitoring wireless sensor network system. Hence, the sensors record the results in real time, allowing us to observe changes immediately and intervene as needed. Therefore, in public places, the use of wireless sensor network systems will have a major positive impact in terms of saving time and money, as well as protecting the health of personnel.
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References
Adgate JL, Church TR, Ryan AD et al (2004) Outdoor, indoor, and personal exposure to VOCs in children. Environ Health Perspect 112:1386–1392. https://doi.org/10.1289/ehp.7107
Aktar T. (2016) Ki̇myasal gaz dolum i̇şlemleri̇nde ri̇skleri̇n beli̇rlenmesi̇ ve ki̇myasal maruzi̇yet ölçümünün yapilmasi
Aktaş Ö, Milli M, Lakestani S, Milli M (2020) Modelling sensor ontology with the SOSA/SSN frameworks: a case study for laboratory parameters. Turk J Electr Eng Comput Sci 28:2566–2585. https://doi.org/10.3906/elk-1912-160
Aktas O, Milli M, Lakestani S, Milli M (2020) Knowledge management system for semantic sensor data. In: 2020 28th signal processing and communications applications conference, SIU 2020-Proceedings. pp 7–10
Ams C (2017) Ultra-low power digital gas sensor for monitoring indoor air quality
Çankaya S, Pekey H, Pekey B, Özerkan Aydın B (2020) Volatile organic compound concentrations and their health risks in various workplace microenvironments. Hum Ecol Risk Assess 26:822–842. https://doi.org/10.1080/10807039.2018.1539638
Demanega I, Mujan I, Singer BC et al (2021) Performance assessment of low-cost environmental monitors and single sensors under variable indoor air quality and thermal conditions. Build Environ 187:107415. https://doi.org/10.1016/j.buildenv.2020.107415
Di Natale C, Macagnano A, Martinelli E et al (2003) Lung cancer identification by the analysis of breath by means of an array of non-selective gas sensors. Biosens Bioelectron 18:1209–1218. https://doi.org/10.1016/S0956-5663(03)00086-1
Dodson RE, Houseman EA, Levy JI et al (2007) Measured and modeled personal exposures to and risks from volatile organic compounds. Environ Sci Technol 41:8498–8505. https://doi.org/10.1021/es071127s
EPA (1999) Determination of volatile organic compounds in ambient air using active sampling onto sorbent tubes.
Haller A, Janowicz K, Cox SJD, et al (2017) Semantic sensor network ontology.
Hazrati S, Rostami R, Farjaminezhad M, Fazlzadeh M (2016) Preliminary assessment of BTEX concentrations in indoor air of residential buildings and atmospheric ambient air in Ardabil. Iran Atmos Environ 132:91–97. https://doi.org/10.1016/j.atmosenv.2016.02.042
Heavner DL, Ogden MW, Nelson PR (1992) Multisorbent thermal desorption/gas chromatography/mass selective detection method for the determination of target volatile organic compounds in indoor air. Environ Sci Technol 26:1737–1746. https://doi.org/10.1021/es00033a004
Isinkaralar K, Turkyilmaz A, Lakestani S (2023) Equilibrium study of benzene, toluene, ethylbenzene, and xylene (BTEX) from gas streams by black pine cones-derived activated carbon. Environ Technol Innov 31:103209. https://doi.org/10.1016/j.eti.2023.103209
Jacobson MZ (2002) Atmospheric pollution, history, science, and regulation. Cambridge university press.
Jin W, Kim DH (2018) Design and implementation of e-health system based on semantic sensor network using IETF YANG. Sensors 18(2):629. https://doi.org/10.3390/s18020629
Joshi SM (2008) The sick building syndrome. Br Med J (Clin Res Ed) 12:61–64. https://doi.org/10.4103/0019-5278.43262
Kaikiti C, Stylianou M, Agapiou A (2022) TD-GC/MS analysis of indoor air pollutants (VOCs, PM) in hair salons. Chemosphere 294:133691. https://doi.org/10.1016/j.chemosphere.2022.133691
Kamani H, Abdipour H, Mohammadi L et al (2023) Health risk assessment of BTEX compounds (benzene, toluene, ethylbenzene and xylene) in different indoor air using Monte Carlo simulation in zahedan city. Iran Heliyon 9:e20294. https://doi.org/10.1016/j.heliyon.2023.e20294
Kapoor NR, Kumar A, Alam T et al (2021) A review on indoor environment quality of indian school classrooms. Sustainability 13(21):11855. https://doi.org/10.3390/su132111855
Lakestani S, Karakas B, AcarVaizoglu S et al (2013) Comparison of indoor and outdoor air quality in children homes at prenatal period and one year old. J Civil Environ Struct Constr Archit Eng 7:275–280. https://doi.org/10.5281/zenodo.1061557
Lee J, Roux S, Descharles N et al (2021) Quantitative determination of volatile compounds using TD-GC-MS and isotope standard addition for application to the heat treatment of food. Food Control 121:107635. https://doi.org/10.1016/j.foodcont.2020.107635
Liu T, Manager B Dht 22 temperature and humidity sernsor datasheet.
Markert sandra (2016) Der Rest, der in der Tube bleibt. 8–9
Massold E, Bähr C, Salthammer T, Brown SK (2005) Determination of VOC and TVOC in air using thermal desorption GC-MS - Practical implications for test chamber experiments. Chromatographia 62:75–85. https://doi.org/10.1365/s10337-005-0582-z
Milli M, Milli M, Lakestani S, Aktas O (2023) Semantic-based anomaly detection in laboratory environments using SOSA/SSN sensor ontology frameworks. Pamukkale Univ J Eng Sci 29:357–369. https://doi.org/10.5505/pajes.2022.95595
Phillips M, Gleeson K, Hughes JMB et al (1999) Volatile organic compounds in breath as markers of lung cancer: a cross-sectional study. Lancet 353(9168):1930–1933
Radiello (2019) English 01–2019. https://content.restek.com/content/published/api/v1.1/assets/CONT8AFE45B3507E40BC902DD153BF9C13C1/native/radiello+Instruction+Manual.pdf?channelToken=6428daeb0e4e4341beecd8e2b41b4d46&download=false
Sofuoglu SC, Sofuoglu A (2011) Ilkögretim Okullarında Bina Içi Çevresel Kalite.Pdf. pp 1751–1766
Soysal GE, Ilce A, Lakestani S et al (2023) Comparison of the effects of surgical smoke on the air quality and on the physical symptoms of operating room staff. Biol Res Nurs 25:444–453. https://doi.org/10.1177/10998004221151157
Srivastava A, Devotta S (2007) Indoor air quality of public places in Mumbai, India in terms of volatile organic compounds. Environ Monit Assess 133:127–138. https://doi.org/10.1007/s10661-006-9566-1
Walgraeve C, Demeestere K, Dewulf J et al (2011) Diffusive sampling of 25 volatile organic compounds in indoor air: uptake rate determination and application in Flemish homes for the elderly. Atmos Environ 45:5828–5836. https://doi.org/10.1016/j.atmosenv.2011.07.007
WHO (1984) Indoor air quality research. Report on a WHO meeting. Stockholm
Acknowledgements
We would like to thank the Scientific Industrial and Technological Applications and Research Centre (SITARC) of Bolu Abant Izzet Baysal University for the utilization of laboratories.
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All authors contributed to the study conception, design, data collection and analysis. Dr. Sanaz Lakestani design and management, methodology and data processing, writing, review, and editing. Assis. Prof. Dr. Mehmet Milli design of wireless sensor networks, software and data processing, writing, review, and editing.
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Not applicable (There is no human or animal subject in this study so no need for ethical approval).
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Editorial responsibility: Shahid Hussain.
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Lakestani, S., Milli, M. Comparison of classical and sensor-based methods for determination of indoor air quality. Int. J. Environ. Sci. Technol. (2024). https://doi.org/10.1007/s13762-024-05708-3
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DOI: https://doi.org/10.1007/s13762-024-05708-3